Spatial multiplexing multiple input and multiple output (MIMO) technique is used to increase the data rate (and spectral efficiency) by transmitting multiple data streams via different spatial paths simultaneously. Spatial combining technique, on the other hand, refers to the technique that combines the same data stream via different spatial paths to enhance signal quality. Spatial multiplexing and spatial combining techniques have been widely employed in mobile communications systems such as IEEE 802.11n (2.4 GHz and 5 GHz) and IEEE 802.11ac (5 GHz). For 802.11n and 802.11ac, the signal wavelength is large comparing to the feature size of objects in the propagation environment. As a result, NLOS signal propagation is dominated by the signal scattering from various objects. Due to the severe scattering, OFDM signal is often used in such systems and the spatial multiplexing and spatial combining are done on a per-tone (per-subcarrier) basis in the digital domain.
For higher frequency systems such as IEEE 802.11ad (60 GHz), the signal propagation characteristics change as the signal wavelength becomes small comparing to the feature size of objects in the propagation environment. As a result, signal propagation is dominated by ray-like propagation with discrete paths in space. The signal quality can be greatly enhanced if either TX or RX antenna beams or both TX and RX antenna beams are directed toward strong spatial signal path. The improved signal quality via aligning the antenna beams with strong spatial signal path manifests both increased signal strength (higher signal-to-noise ratio) and reduced delay spread. Since the delay spread is reduced, spatial combining can be wholly or partially done in RF domain (instead of digital domain) to simplify implementation.
In general, phased-array antenna with steerable antenna beam in MIMO operation provides antenna gain and enables mobility. Eigen-beamforming is one method of antenna beam training. The Eigen-beamforming requires transmitter and receiver to estimate the channel response matrix first. The channel response matrix is then decomposed using singular value decomposition (SVD). The MIMO operation uses n dominant Eigen modes (corresponding to n spatial paths) for transmitting n spatial streams. The Eigen beamforming method suffers from the problem that the channel response matrix is obtained in lower signal-to-noise condition since no beamforming is used during the channel estimation.
Another method of antenna beam training is multi-stage iterative training using power method. In the power method, the receiver sends back the normalized receive vector in the n antennas to the transmitter. The transmitter uses the receive vector as the next transmit antenna weight. The antenna weight quickly converges to the first Eigen vector after a few iterations. This process continues until the n vectors (antenna weight vectors) are obtained. The power method suffers from the problem that it only works (converges) in the presence of high signal-to-noise ratio.
The beam training protocol provided in IEEE 802.11ad involves either transmitter or receiver to sweep through a number of antenna beam directions to determine the beam with the best signal quality. For efficient beam training, multiple stages of beam training are provided. The initial stage, called the SLS (sector level sweep), provides coarse antenna beam training. The subsequent stage, called the beam refinement protocol or beam tracking, provides the fine-tuning of antenna beam for improved pointing accuracy and higher signal quality. These beam training protocols are generally used to train a single spatial beam for the transmission of a single data stream.
A solution is sought for training multiple antenna beam combinations to allow for multiple data streams for increased data rate, or to allow combining of the same data stream for enhanced signal quality.